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Registration of dense matched point cloud from UAV-borne images
Author(s): Wang Tao
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Paper Abstract

Due to the unprecedented technology development of sensors, platforms and algorithms for 3D data acquisition and generation, airborne and close-range data, in the form of image based, Light Detection and Ranging (LiDAR) based point clouds, Digital Elevation Models (DEM) and 3D city models, become more accessible than ever before. Change detection or time-series data analysis in 3D has gained great attention due to its capability of providing volumetric dynamics to facilitate more applications and provide more accurate results. We try to use mini-UAV platforms to detect change in unauthorized construction. Use of direct geo-referencing data leads to registration failure between dense matched point cloud captured by mini-UAV platforms because of low-cost sensors. This paper therefore proposes a registration method for dense matched point cloud. We try to extract sift points in the images from different times, then we match points to get the same point. By using this method, we can get control points in the cloud point. Finally, we register the cloud points successfully.

Paper Details

Date Published: 9 August 2018
PDF: 5 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108062G (9 August 2018); doi: 10.1117/12.2502862
Show Author Affiliations
Wang Tao, Guangzhou Institute of Geography (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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